URL: https://{s}.google.com/vt/lyrs={l}&x={x}&y={y}&z={z}
Parameters:
- Subdomain: mt0, mt1, mt2, mt3
- Layer:
- m = standard roadmap
- r = alternative roadmap
- h = roads only
ClojureScript master now has cljs.core/eval. This delegates to cljs.core/*eval* which, by default throws, but you can bind it to any implementation that can compile and evaluate ClojureScript forms.
If you require the cljs.js namespace (which is the main support namespace for self-hosted ClojureScript), then cljs.core/*eval* is set to an implementation that uses self-hosted ClojureScript for this capability. This means that all self-hosted ClojureScript environments will now have a first-class eval implementation that just works. For example, Planck master:
$ planck -q
cljs.user=> (eval '(+ 2 3))
5
| name | japanese-tech-writing |
|---|---|
| description | 日本語の技術文書・書籍原稿の文章規範。段落と論証の構成(パラグラフライティング)、論証の厳密さ(ツッコミどころの除去)、読み手の負荷の管理、視点と語り、演出の抑制、LLM っぽい空句の禁止、翻訳調の比喩と擬人化の禁止(「運ぶ」「効く」「開かれた問い」など)、冗長の排除を定める。日本語で技術書の章、草稿、記事、解説文を書くとき、または推敲・リライトするときに使用する。 |
| license | Unlicense(https://gist.github.com/k16shikano/67625f2a7d96e3bbdfae8d571a936063) |
日本語で技術的な原稿(書籍の章、記事、解説文)を書く・推敲するときは、以下の規範に従う。
| Senior Data Scientist | |
| VM507:1 Lead, Solution Architecture - Artificial Intelligence | |
| VM507:1 Data Scientist - Senior Associate - new | |
| VM507:1 Postdoctoral Appointee - Algorithm Optimization at the Exasc... | |
| VM507:1 Postdoctoral Appointee - Machine Learning | |
| VM507:1 Elasticsearch, Forensic Analytics - Manager | |
| VM507:1 Senior Manager - AI/Data Scientist Pre-Sales Architect - new | |
| VM507:1 Elasticsearch, Forensic Analytics - Senior Consultant | |
| VM507:1 Data Scientist | |
| Experienced Scientific Software Engineer (Machine Learning)Promoted |
Who this is for: an AI agent (or engineer) helping someone build an illustrated, animated floorplan dashboard for Home Assistant from scratch, with their own house, their own illustrations, their own sensors.
How to read it: it is written as questions and answers. Find the question the user is really asking and answer from that section. The numbers, room names and entity IDs here are placeholders — every one of them will be different in a new build. What transfers is the method: the canvas rule, the file naming scheme,
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
| #!/bin/bash | |
| # Install an SSH key on an instance automatically and then configure an | |
| # SSM proxy to the instance which will be used by SSH. | |
| # | |
| # Copy this script to ~/.ssh/ssm-proxy and make it executable: | |
| # | |
| # chmod +x ~/.ssh/ssm-proxy | |
| # | |
| # This script should be set as the ProxyCommand. For example: | |
| # |
| // SoA and SSE separating axis test between two convex hulls. Face phases go through a SIMD | |
| // getSupport. For the edge phase, B's verts and face normals are transformed into A's space once | |
| // up front from the hull's stored SoA arrays so the inner loop does no transforms. Data is packed | |
| // one array per component and the loop tests one B edge against four A edges at a time. Edge | |
| // counts are bounded so every buffer is a fixed size stack array. | |
| #include "sat.h" | |
| #include <immintrin.h> | |
| // a*b + c, fused when FMA is available. | |
| static inline __m128 mad(__m128 a, __m128 b, __m128 c) |